Long-term prognosis and its associated predictive factors in patients with eosinophilic gastroenteritis

BACKGROUND Eosinophilic gastroenteritis(EGE)is a chronic recurrent disease with abnormal eosinophilic infiltration in the gastrointestinal tract.Glucocorticoids remain the most common treatment method.However,disease relapse and glucocorticoid dependence remain notable problems.To date,few studies have illuminated the prognosis of EGE and risk factors for disease relapse.AIM To describe the clinical characteristics of EGE and possible predictive factors for disease relapse based on long-term follow-up.METHODS This was a retrospective cohort study of 55 patients diagnosed with EGE admitted to one medical center between 2013 and 2022.Clinical records were collected and analyzed.Kaplan-Meier curves and log-rank tests were conducted to reveal the risk factors for long-term relapse-free survival(RFS).RESULTS EGE showed a median onset age of 38 years and a slight female predominance(56.4%).The main clinical symptoms were abdominal pain(89.1%),diarrhea(61.8%),nausea(52.7%),distension(49.1%)and vomiting(47.3%).Forty-three(78.2%)patients received glucocorticoid treatment,and compared with patients without glucocorticoid treatments,they were more likely to have elevated serum immunoglobin E(IgE)(86.8%vs 50.0%,P=0.022)and descending duodenal involvement(62.8%vs 27.3%,P=0.046)at diagnosis.With a median follow-up of 67 mo,all patients survived,and 56.4%had at least one relapse.Six variables at baseline might have been associated with the overall RFS rate,including age at diagnosis<40 years[hazard ratio(HR)2.0408,95%confidence interval(CI):1.0082–4.1312,P=0.044],body mass index(BMI)>24 kg/m^(2)(HR 0.3922,95%CI:0.1916-0.8027,P=0.014),disease duration from symptom onset to diagnosis>3.5 mo(HR 2.4725,95%CI:1.220-5.0110,P=0.011),vomiting(HR 3.1259,95%CI:1.5246-6.4093,P=0.001),total serum IgE>300 KU/L at diagnosis(HR 0.2773,95%CI:0.1204-0.6384,P=0.022)and glucocorticoid treatment(HR 6.1434,95%CI:2.8446-13.2676,P=0.003).CONCLUSION In patients with EGE,younger onset age,longer disease course,vomiting and glucocorticoid treatment were risk factors for disease relapse,whereas higher BMI and total IgE level at baseline were protective.

Correlative factors of poor prognosis and abnormal cellular immune function in patients with Alzheimer’s disease

BACKGROUND Alzheimer’s disease(AD)is a serious disease causing human dementia and social problems.The quality of life and prognosis of AD patients have attracted much attention.The role of chronic immune inflammation in the pathogenesis of AD is becoming more and more important.AIM To study the relationship among cognitive dysfunction,abnormal cellular immune function,neuroimaging results and poor prognostic factors in patients.METHODS A retrospective analysis of 62 hospitalized patients clinical diagnosed with AD who were admitted to our hospital from November 2015 to November 2020.Collect cognitive dysfunction performance characteristics,laboratory test data and neuroimaging data from medical records within 24 h of admission,including Mini Mental State Examination Scale score,drawing clock test,blood T lymphocyte subsets,and neutrophils and lymphocyte ratio(NLR),disturbance of consciousness,extrapyramidal symptoms,electroencephalogram(EEG)and head nucleus magnetic spectroscopy(MRS)and other data.Multivariate logistic regression analysis was used to determine independent prog-nostic factors.the modified Rankin scale(mRS)was used to determine whether the prognosis was good.The correlation between drug treatment and prognostic mRS score was tested by the rank sum test.RESULTS Univariate analysis showed that abnormal cellular immune function,extrapyramidal symptoms,obvious disturbance of consciousness,abnormal EEG,increased NLR,abnormal MRS,and complicated pneumonia were related to the poor prognosis of AD patients.Multivariate logistic regression analysis showed that the decrease in the proportion of T lym-phocytes in the blood after abnormal cellular immune function(odd ratio:2.078,95%confidence interval:1.156-3.986,P<0.05)was an independent risk factor for predicting the poor prognosis of AD.The number of days of donepezil treatment to improve cognitive function was negatively correlated with mRS score(r=0.578,P<0.05).CONCLUSION The decrease in the proportion of T lymphocytes may have predictive value for the poor prognosis of AD.It is recommended that the proportion of T lymphocytes<55%is used as the cut-off threshold for predicting the poor prog-nosis of AD.The early and continuous drug treatment is associated with a good prognosis.

Clinical manifestations,diagnosis and long-term prognosis of adult autoimmune enteropathy:Experience from Peking Union Medical College Hospital

BACKGROUND Autoimmune enteropathy(AIE)is a rare disease whose diagnosis and long-term prognosis remain challenging,especially for adult AIE patients.AIM To improve overall understanding of this disease’s diagnosis and prognosis.METHODS We retrospectively analyzed the clinical,endoscopic and histopathological characteristics and prognoses of 16 adult AIE patients in our tertiary medical center between 2011 and 2023,whose diagnosis was based on the 2007 diagnostic criteria.RESULTS Diarrhea in AIE patients was characterized by secretory diarrhea.The common endoscopic manifestations were edema,villous blunting and mucosal hyperemia in the duodenum and ileum.Villous blunting(100%),deep crypt lymphocytic infiltration(67%),apoptotic bodies(50%),and mild intraepithelial lymphocytosis(69%)were observed in the duodenal biopsies.Moreover,there were other remarkable abnormalities,including reduced or absent goblet cells(duodenum 94%,ileum 62%),reduced or absent Paneth cells(duodenum 94%,ileum 69%)and neutrophil infiltration(duodenum 100%,ileum 69%).Our patients also fulfilled the 2018 diagnostic criteria but did not match the 2022 diagnostic criteria due to undetectable anti-enterocyte antibodies.All patients received glucocorticoid therapy as the initial medication,of which 14/16 patients achieved a clinical response in 5(IQR:3-20)days.Immunosuppressants were administered to 9 patients with indications of steroid dependence(6/9),steroid refractory status(2/9),or intensified maintenance medication(1/9).During the median of 20.5 months of followup,2 patients died from multiple organ failure,and 1 was diagnosed with non-Hodgkin’s lymphoma.The cumulative relapse-free survival rates were 62.5%,55.6%and 37.0%at 6 months,12 months and 48 months,respectively.CONCLUSION Certain histopathological findings,including a decrease or disappearance of goblet and Paneth cells in intestinal biopsies,might be potential diagnostic criteria for adult AIE.The long-term prognosis is still unsatisfactory despite corticosteroid and immunosuppressant medications,which highlights the need for early diagnosis and novel medications.

Bioinformatics analysis and experimental validation of cystathionine-gamma-lyase as a potential prognosis biomarker in hepatocellular carcinoma

Background:Hepatocellular carcinoma(HCC)is a common malignant tumor with poor prognosis and high mortality worldwide.Although cystathionine-gamma-lyase(CSE)plays an important role in the development of multiple tumors,the clinical implication and potential mechanisms of CSE in HCC development remain elusive.Methods:In our study,the CSE expression in HCC was analyzed in Gene Expression Omnibus(GEO)and The Cancer Genome Atlas(TCGA)datasets and further confirmed by RT-qPCR and immunohistochemistry assays in HCC samples.Furthermore,the associations between CSE expression and HCC malignancy as well as survival were analyzed in GSE14520 and validated in HCC patients.Finally,the biological functions of CSE in HCC cells was assessed by CCK-8,flow cytometry and Western blotting.Results:Lower transcriptional and proteomic CSE expressions were found in HCC tissues in contrast to adjacent normal tissues.Decreased CSE mRNA expression was significantly associated with advanced clinicopathological features and poor outcomes in HCC patients from public database and our cohort.Following univariate and multivariate analyses of GSE14520 data showed that CSE expression was an independent prognostic indicator for the overall survival(OS)and recurrence-free survival(RFS)of HCC patients.In vitro experiments further explained that CSE might trigger HCC cell apoptosis by H2S.Conclusion:In summary,the present study identified the relationship between CSE expression and HCC malignancy as well as OS and RFS,indicating that CSE might be a potential prognostic biomarker and a novel therapeutic target for HCC.

Identification of cell surface markers for acute myeloid leukemia prognosis based on multi-model analysis

Given the extremely high inter-patient heterogeneity of acute myeloid leukemia(AML),the identification of biomarkers for prognostic assessment and therapeutic guidance is critical.Cell surface markers(CSMs)have been shown to play an important role in AML leukemogenesis and progression.In the current study,we evaluated the prognostic potential of all human CSMs in 130 AML patients from The Cancer Genome Atlas(TCGA)based on differential gene expression analysis and univariable Cox proportional hazards regression analysis.By using multi-model analysis,including Adaptive LASSO regression,LASSO regression,and Elastic Net,we constructed a 9-CSMs prognostic model for risk stratification of the AML patients.The predictive value of the 9-CSMs risk score was further validated at the transcriptome and proteome levels.Multivariable Cox regression analysis showed that the risk score was an independent prognostic factor for the AML patients.The AML patients with high 9-CSMs risk scores had a shorter overall and event-free survival time than those with low scores.Notably,single-cell RNA-sequencing analysis indicated that patients with high 9-CSMs risk scores exhibited chemotherapy resistance.Furthermore,PI3K inhibitors were identified as potential treatments for these high-risk patients.In conclusion,we constructed a 9-CSMs prognostic model that served as an independent prognostic factor for the survival of AML patients and held the potential for guiding drug therapy.

Marker Ki-67 is a potential biomarker for the diagnosis and prognosis of prostate cancer based on two cohorts

BACKGROUND Prostate cancer(PCa)is a widespread malignancy,predominantly affecting elderly males,and current methods for diagnosis and treatment of this disease continue to fall short.The marker Ki-67(MKI67)has been previously demonstrated to correlate with the proliferation and metastasis of various cancer cells,including those of PCa.Hence,verifying the association between MKI67 and the diagnosis and prognosis of PCa,using bioinformatics databases and clinical data analysis,carries significant clinical implications.AIM To explore the diagnostic and prognostic efficacy of antigens identified by MKI67 expression in PCa.METHODS For cohort 1,the efficacy of MKI67 diagnosis was evaluated using data from The Cancer Genome Atlas(TCGA)and Genotype-Tissue Expression(GTEx)databases.For cohort 2,the diagnostic and prognostic power of MKI67 expression was further validated using data from 271 patients with clinical PCa.RESULTS In cohort 1,MKI67 expression was correlated with prostate-specific antigen(PSA),Gleason Score,T stage,and N stage.The receiver operating characteristic(ROC)curve showed a strong diagnostic ability,and the Kaplan-Meier method demonstrated that MKI67 expression was negatively associated with the progression-free interval(PFI).The time-ROC curve displayed a weak prognostic capability for MKI67 expression in PCa.In cohort 2,MKI67 expression was significantly related to the Gleason Score,T stage,and N stage;however,it was negatively associated with the PFI.The time-ROC curve revealed the stronger prognostic capability of MKI67 in patients with PCa.Multivariate COX regression analysis was performed to select risk factors,including PSA level,N stage,and MKI67 expression.A nomogram was established to predict the 3-year PFI.CONCLUSION MKI67 expression was positively associated with the Gleason Score,T stage,and N stage and showed a strong diagnostic and prognostic ability in PCa.

Ferroptosis biomarkers predict tumor mutation burden's impact on prognosis in HER2-positive breast cancer

BACKGROUND Ferroptosis has recently been associated with multiple degenerative diseases.Ferroptosis induction in cancer cells is a feasible method for treating neoplastic diseases.However,the association of iron proliferation-related genes with prognosis in HER2+breast cancer(BC)patients is unclear.AIM To identify and evaluate fresh ferroptosis-related biomarkers for HER2+BC.METHODS First,we obtained the mRNA expression profiles and clinical information of HER2+BC patients from the TCGA and METABRIC public databases.A four gene prediction model comprising PROM2,SLC7A11,FANCD2,and FH was subsequently developed in the TCGA cohort and confirmed in the METABRIC cohort.Patients were stratified into high-risk and low-risk groups based on their median risk score,an independent predictor of overall survival(OS).Based on these findings,immune infiltration,mutations,and medication sensitivity were analyzed in various risk groupings.Additionally,we assessed patient prognosis by combining the tumor mutation burden(TMB)with risk score.Finally,we evaluated the expression of critical genes by analyzing single-cell RNA sequencing(scRNA-seq)data from malignant vs normal epithelial cells.RESULTS We found that the higher the risk score was,the worse the prognosis was(P<0.05).We also found that the immune cell infiltration,mutation,and drug sensitivity were different between the different risk groups.The highrisk subgroup was associated with lower immune scores and high TMB.Moreover,we found that the combination of the TMB and risk score could stratify patients into three groups with distinct prognoses.HRisk-HTMB patients had the worst prognosis,whereas LRisk-LTMB patients had the best prognosis(P<0.0001).Analysis of the scRNAseq data showed that PROM2,SLC7A11,and FANCD2 were significantly differentially expressed,whereas FH was not,suggesting that these genes are expressed mainly in cancer epithelial cells(P<0.01).CONCLUSION Our model helps guide the prognosis of HER2+breast cancer patients,and its combination with the TMB can aid in more accurate assessment of patient prognosis and provide new ideas for further diagnosis and treatment.

Exploring impedance spectrum for lithium-ion batteries diagnosis and prognosis:A comprehensive review

Lithium-ion batteries have extensive usage in various energy storage needs,owing to their notable benefits of high energy density and long lifespan.The monitoring of battery states and failure identification are indispensable for guaranteeing the secure and optimal functionality of the batteries.The impedance spectrum has garnered growing interest due to its ability to provide a valuable understanding of material characteristics and electrochemical processes.To inspire further progress in the investigation and application of the battery impedance spectrum,this paper provides a comprehensive review of the determination and utilization of the impedance spectrum.The sources of impedance inaccuracies are systematically analyzed in terms of frequency response characteristics.The applicability of utilizing diverse impedance features for the diagnosis and prognosis of batteries is further elaborated.Finally,challenges and prospects for future research are discussed.

Circulating tumor DNA and its role in detection, prognosis and therapeutics of hepatocellular carcinoma

Hepatocellular carcinoma(HCC) is considered the fifth most prevalent cancer among all types of cancers and has the third most morbidity value. It has the most frequent duplication time and a high recurrence rate. Recently, the most unique technique used is liquid biopsies, which carry many markers;the most prominent is circulating tumor DNA(ctDNA). Varied methods are used to investigate ctDNA, including various forms of polymerase chain reaction(PCR) [emulsion PCR(ePCR), digital PCR(dPCR), and bead, emulsion, amplification, magnetic(BEAMing) PCR]. Hence ctDNA is being recognized as a potential biomarker that permits early cancer detection,treatment monitoring, and predictive data on tumor burden are subjective to therapy or surgery. Numerous ctDNA biomarkers have been investigated based on their alterations such as 1) single nucleotide variations(either insertion or deletion of a nucleotide) markers including TP53, KRAS, and CCND1;2) copy number variations which include markers such as CDK6, EFGR, MYC and BRAF;3) DNA methylation(RASSF1A, SEPT9, KMT2C and CCNA2);4) homozygous mutation includes ctDNA markers as CDKN2A, AXIN1;and 5) gain or loss of function of the genes, particularly for HCC. Various researchers have conducted many studies and gotten fruitful results.Still, there are some drawbacks to ctDNA namely low quantity, fragment heterogeneity, less stability, limited mutant copies and standards, and differential sensitivity. However, plenty of investigations demonstrate ctDNA's significance as a polyvalent biomarker for cancer and can be viewed as a future diagnostic, prognostic and therapeutic agent. This article overviews many conditions in genetic changes linked to the onset and development of HCC, such as dysregulated signaling pathways, somatic mutations, single-nucleotide polymorphisms, and genomic instability. Additionally, efforts are also made to develop treatments for HCC that are molecularly targeted and to unravel some of the genetic pathways that facilitate its early identification.

Predicting the Prognosis and Immunotherapeutic Response of Triple-Negative Breast Cancer by Constructing a Prognostic Model Based on CD8+T Cell-Related Immune Genes

Objective Triple-negative breast cancer(TNBC)poses a significant challenge for treatment efficacy.CD8+T cells,which are pivotal immune cells,can be effectively analyzed for differential gene expression across diverse cell populations owing to rapid advancements in sequencing technology.By leveraging these genes,our objective was to develop a prognostic model that accurately predicts the prognosis of patients with TNBC and their responsiveness to immunotherapy.Methods Sample information and clinical data of TNBC were sourced from The Cancer Genome Atlas and METABRIC databases.In the initial stage,we identified 67 differentially expressed genes associated with immune response in CD8+T cells.Subsequently,we narrowed our focus to three key genes,namely CXCL13,GBP2,and GZMB,which were used to construct a prognostic model.The accuracy of the model was assessed using the validation set data and receiver operating characteristic(ROC)curves.Furthermore,we employed various methods,including Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway,immune infiltration,and correlation analyses with CD274(PD-L1)to explore the model's predictive efficacy in immunotherapeutic responses.Additionally,we investigated the potential underlying biological pathways that contribute to divergent treatment responses.Results We successfully developed a model capable of predicting the prognosis of patients with TNBC.The areas under the curve(AUC)values for the 1-,3-,and 5-year survival predictions were 0.618,0.652,and 0.826,respectively.Employing this risk model,we stratified the samples into high-and low-risk groups.Through KEGG enrichment analysis,we observed that the high-risk group predominantly exhibited enrichment in metabolism-related pathways such as drug and chlorophyll metabolism,whereas the low-risk group demonstrated significant enrichment in cytokine pathways.Furthermore,immune landscape analysis revealed noteworthy variations between(PD-L1)expression and risk scores,indicating that our model effectively predicted the response of patients to immune-based treatments.Conclusion Our study demonstrates the potential of CXCL13,GBP2,and GZMB as prognostic indicators of clinical outcomes and immunotherapy responses in patients with TNBC.These findings provide valuable insights and novel avenues for developing immunotherapeutic approaches targeting TNBC.

Digital pathology-based artificial intelligence models for differential diagnosis and prognosis of sporadic odontogenic keratocysts

Odontogenic keratocyst(OKC)is a common jaw cyst with a high recurrence rate.OKC combined with basal cell carcinoma as well as skeletal and other developmental abnormalities is thought to be associated with Gorlin syndrome.Moreover,OKC needs to be differentiated from orthokeratinized odontogenic cyst and other jaw cysts.Because of the different prognosis,differential diagnosis of several cysts can contribute to clinical management.We collected 519 cases,comprising a total of 2157 hematoxylin and eosinstained images,to develop digital pathology-based artificial intelligence(AI)models for the diagnosis and prognosis of OKC.The Inception_v3 neural network was utilized to train and test models developed from patch-level images.Finally,whole slide imagelevel AI models were developed by integrating deep learning-generated pathology features with several machine learning algorithms.The AI models showed great performance in the diagnosis(AUC=0.935,95%CI:0.898–0.973)and prognosis(AUC=0.840,95%CI:0.751–0.930)of OKC.The advantages of multiple slides model for integrating of histopathological information are demonstrated through a comparison with the single slide model.Furthermore,the study investigates the correlation between AI features generated by deep learning and pathological findings,highlighting the interpretative potential of AI models in the pathology.Here,we have developed the robust diagnostic and prognostic models for OKC.The AI model that is based on digital pathology shows promise potential for applications in odontogenic diseases of the jaw.

Novel lactylation-related signature to predict prognosis for pancreatic adenocarcinoma

BACKGROUND Lactate,previously considered a metabolic byproduct,is pivotal in cancer progression and maintaining the immunosuppressive tumor microenvironment.Further investigations confirmed that lactate is a primary regulator,introducing recently described post-translational modifications of histone and non-histone proteins,termed lysine lactylation.Pancreatic adenocarcinomas are characterized by increased glycolysis and lactate accumulation.However,our understanding of lactylation-related genes in pancreatic adenocarcinomas remains limited.AIM To construct a novel lactylation-related gene signature to predict the survival of patients with pancreatic cancer.METHODS RNA-seq and clinical data of pancreatic adenocarcinoma(PDAC)were obtained from the GTEx(Genotype-Tissue Expression)and TCGA(The Cancer Genome Atlas)databases via Xena Explorer,and GSE62452 datasets from GEO.Data on lactylation-related genes were obtained from publicly available sources.Differential expressed genes(DEGs)were acquired by using R package“DESeq2”in R.Univariate COX regression analysis,LASSO Cox and multivariate Cox regressions were produced to construct the lactylation-related prognostic model.Further analyses,including functional enrichment,ESTIMATE,and CIBERSORT,were performed to analyze immune status and treatment responses in patients with pancreatic cancer.PDAC and normal human cell lines were subjected to western blot analysis under lactic acid intervention;two PDAC cell lines with the most pronounced lactylation were selected.Subsequently,RT-PCR was employed to assess the expression of LRGs genes;SLC16A1,which showed the highest expression,was selected for further investigation.SLC16A1-mediated lactylation was analyzed by immunofluorescence,lactate production analysis,colony formation,transwell,and wound healing assays to investigate its role in promoting the proliferation and migration of PDAC cells.In vivo validation was performed using an established tumor model.RESULTS In this study,we successfully identified 10 differentially expressed lactylation-related genes(LRGs)with prognostic value.Subsequently,a lactylation-related signature was developed based on five OS-related lactylationrelated genes(SLC16A1,HLA-DRB1,KCNN4,KIF23,and HPDL)using Lasso Cox hazard regression analysis.Subsequently,we evaluated the clinical significance of the lactylation-related genes in pancreatic adenocarcinoma.A comprehensive examination of infiltrating immune cells and tumor mutation burden was conducted across different subgroups.Furthermore,we demonstrated that SLC16A1 modulates lactylation in pancreatic cancer cells through lactate transport.Both in vivo and in vitro experiments showed that decreasing SLC16A1 Level and its lactylation significantly inhibited tumor progression,indicating the potential of targeting the SLC16A1/Lactylation-associated signaling pathway as a therapeutic strategy against pancreatic adenocarcinoma.CONCLUSION We constructed a novel lactylation-related prognostic signature to predict OS,immune status,and treatment response of patients with pancreatic adenocarcinoma,providing new strategic directions and antitumor immunotherapies.

Glucose metabolic reprogramming-related parameters for the prediction of 28-day neurological prognosis and all-cause mortality in patients after cardiac arrest:a prospective single-center observational study

BACKGROUND:We aimed to observe the dynamic changes in glucose metabolic reprogrammingrelated parameters and their ability to predict neurological prognosis and all-cause mortality in cardiac arrest patients after the restoration of spontaneous circulation(ROSC).METHODS:Adult cardiac arrest patients after ROSC who were admitted to the emergency or cardiac intensive care unit of the First Aflliated Hospital of Dalian Medical University from August 1,2017,to May 30,2021,were enrolled.According to 28-day survival,the patients were divided into a non-survival group(n=82) and a survival group(n=38).Healthy adult volunteers(n=40) of similar ages and sexes were selected as controls.The serum levels of glucose metabolic reprogrammingrelated parameters(lactate dehydrogenase [LDH],lactate and pyruvate),neuron-specific enolase(NSE) and interleukin 6(IL-6) were measured on days 1,3,and 7 after ROSC.The Acute Physiology and Chronic Health Evaluation II(APACHE II) score and Sequential Organ Failure Assessment(SOFA) score were calculated.The Cerebral Performance Category(CPC) score was recorded on day 28 after ROSC.RESULTS:Following ROSC,the serum LDH(607.0 U/L vs.286.5 U/L),lactate(5.0 mmol/L vs.2.0 mmol/L),pyruvate(178.0 μmol/L vs.70.9 μmol/L),and lactate/pyruvate ratio(34.1 vs.22.1) significantly increased and were higher in the non-survivors than in the survivors on admission(all P<0.05).Moreover,the serum LDH,pyruvate,IL-6,APACHE II score,and SOFA score on days 1,3 and 7 after ROSC were significantly associated with 28-day poor neurological prognosis and 28-day all-cause mortality(all P<0.05).The serum LDH concentration on day 1 after ROSC had an area under the receiver operating characteristic curve(AUC) of 0.904 [95% confidence interval [95% CI]:0.851–0.957]) with 96.8% specificity for predicting 28-day neurological prognosis and an AUC of 0.950(95% CI:0.911–0.989) with 94.7% specificity for predicting 28-day all-cause mortality,which was the highest among the glucose metabolic reprogramming-related parameters tested.CONCLUSION:Serum parameters related to glucose metabolic reprogramming were significantly increased after ROSC.Increased serum LDH and pyruvate levels,and lactate/pyruvate ratio may be associated with 28-day poor neurological prognosis and all-cause mortality after ROSC,and the predictive eflcacy of LDH during the first week was superior to others.

NAD+associated genes as potential biomarkers for predicting the prognosis of gastric cancer

Nicotinamide adenine dinucleotide(NAD+)plays an essential role in cellular metabolism,mitochondrial homeostasis,inflammation,and senescence.However,the role of NAD+-regulated genes,including coding and long non-coding genes in cancer development is poorly understood.We constructed a prediction model based on the expression level of NAD+metabolism-related genes(NMRGs).Furthermore,we validated the expression of NMRGs in gastric cancer(GC)tissues and cell lines;additionally,β-nicotinamide mononucleotide(NMN),a precursor of NAD+,was used to treat the GC cell lines to analyze its effects on the expression level of NMRGs lncRNAs and cellular proliferation,cell cycle,apoptosis,and senescence-associated secretory phenotype(SASP).A total of 13 NMRGs-related lncRNAs were selected to construct prognostic risk signatures,and patients with high-risk scores had a poor prognosis.Some immune checkpoint genes were upregulated in the high-risk group.In addition,cell cycle,epigenetics,and senescence were significantly downregulated in the high-risk group.Notably,we found that the levels of immune cell infiltration,including CD8 T cells,CD4 naïve T cells,CD4 memory-activated T cells,B memory cells,and naïve B cells,were significantly associated with risk scores.Furthermore,the treatment of NMN showed increased proliferation of AGS and MKN45 cells.In addition,the expression of SASP factors(IL6,IL8,IL10,TGF-β,and TNF-α)was significantly decreased after NMN treatment.We conclude that the lncRNAs associated with NAD+metabolism can potentially be used as biomarkers for predicting clinical outcomes of GC patients.

GATIS score for predicting the prognosis of rectal neuroendocrine neoplasms:A Chinese multicenter study of 12-year experience

BACKGROUND There is currently a shortage of accurate,efficient,and precise predictive instruments for rectal neuroendocrine neoplasms(NENs).AIM To develop a predictive model for individuals with rectal NENs(R-NENs)using data from a large cohort.METHODS Data from patients with primary R-NENs were retrospectively collected from 17 large-scale referral medical centers in China.Random forest and Cox proportional hazard models were used to identify the risk factors for overall survival and progression-free survival,and two nomograms were constructed.RESULTS A total of 1408 patients with R-NENs were included.Tumor grade,T stage,tumor size,age,and a prognostic nutritional index were important risk factors for prognosis.The GATIS score was calculated based on these five indicators.For overall survival prediction,the respective C-indexes in the training set were 0.915(95%confidence interval:0.866-0.964)for overall survival prediction and 0.908(95%confidence interval:0.872-0.944)for progression-free survival prediction.According to decision curve analysis,net benefit of the GATIS score was higher than that of a single factor.The time-dependent area under the receiver operating characteristic curve showed that the predictive power of the GATIS score was higher than that of the TNM stage and pathological grade at all time periods.CONCLUSION The GATIS score had a good predictive effect on the prognosis of patients with R-NENs,with efficacy superior to that of the World Health Organization grade and TNM stage.

Development of a nomogram for predicting liver transplantation prognosis in hepatocellular carcinoma

BACKGROUND At present,liver transplantation(LT)is one of the best treatments for hepatocellular carcinoma(HCC).Accurately predicting the survival status after LT can significantly improve the survival rate after LT,and ensure the best way to make rational use of liver organs.AIM To develop a model for predicting prognosis after LT in patients with HCC.METHODS Clinical data and follow-up information of 160 patients with HCC who underwent LT were collected and evaluated.The expression levels of alphafetoprotein(AFP),des-gamma-carboxy prothrombin,Golgi protein 73,cytokeratin-18 epitopes M30 and M65 were measured using a fully automated chemiluminescence analyzer.The best cutoff value of biomarkers was determined using the Youden index.Cox regression analysis was used to identify the independent risk factors.A forest model was constructed using the random forest method.We evaluated the accuracy of the nomogram using the area under the curve,using the calibration curve to assess consistency.A decision curve analysis(DCA)was used to evaluate the clinical utility of the nomograms.RESULTS The total tumor diameter(TTD),vascular invasion(VI),AFP,and cytokeratin-18 epitopes M30(CK18-M30)were identified as important risk factors for outcome after LT.The nomogram had a higher predictive accuracy than the Milan,University of California,San Francisco,and Hangzhou criteria.The calibration curve analyses indicated a good fit.The survival and recurrence-free survival(RFS)of high-risk groups were significantly lower than those of low-and middle-risk groups(P<0.001).The DCA shows that the model has better clinical practicability.CONCLUSION The study developed a predictive nomogram based on TTD,VI,AFP,and CK18-M30 that could accurately predict overall survival and RFS after LT.It can screen for patients with better postoperative prognosis,and improve longterm survival for LT patients.

Identification of an immune-related gene signature for predicting prognosis and immunotherapy efficacy in liver cancer via cell-cell communication

BACKGROUND Liver cancer is one of the deadliest malignant tumors worldwide.Immunotherapy has provided hope to patients with advanced liver cancer,but only a small fraction of patients benefit from this treatment due to individual differences.Identifying immune-related gene signatures in liver cancer patients not only aids physicians in cancer diagnosis but also offers personalized treatment strategies,thereby improving patient survival rates.Although several methods have been developed to predict the prognosis and immunotherapeutic efficacy in patients with liver cancer,the impact of cell-cell interactions in the tumor microenvir-onment has not been adequately considered.AIM To identify immune-related gene signals for predicting liver cancer prognosis and immunotherapy efficacy.METHODS Cell grouping and cell-cell communication analysis were performed on single-cell RNA-sequencing data to identify highly active cell groups in immune-related pathways.Highly active immune cells were identified by intersecting the highly active cell groups with B cells and T cells.The significantly differentially expressed genes between highly active immune cells and other cells were subsequently selected as features,and a least absolute shrinkage and selection operator(LASSO)regression model was constructed to screen for diagnostic-related features.Fourteen genes that were selected more than 5 times in 10 LASSO regression experiments were included in a multivariable Cox regression model.Finally,3 genes(stathmin 1,cofilin 1,and C-C chemokine ligand 5)significantly associated with survival were identified and used to construct an immune-related gene signature.RESULTS The immune-related gene signature composed of stathmin 1,cofilin 1,and C-C chemokine ligand 5 was identified through cell-cell communication.The effectiveness of the identified gene signature was validated based on experi-mental results of predictive immunotherapy response,tumor mutation burden analysis,immune cell infiltration analysis,survival analysis,and expression analysis.CONCLUSION The findings suggest that the identified gene signature may contribute to a deeper understanding of the activity patterns of immune cells in the liver tumor microenvironment,providing insights for personalized treatment strategies.

Glycogen metabolism-mediated intercellular communication in the tumor microenvironment influences liver cancer prognosis

Glycogen metabolism plays a key role in the development of hepatoellular carcinoma(HCC),but the function of glycogen metabolism genes in the tumor microenvironment(TME)is still to be elucidated.Single cell RNA-seq data were obtained from ten HCC tumor samples totaling 64,545 cells and 65 glycogen metabolism genes were analyzed bya nonnegative matrix factorization(NMF).The prognosis and immune response of new glycogen TME cell dusters were predicted by using HCC and immunotherapy cohorts from public databases.HOC single cell analysis was divided into fibroblasts,NT T cells,macrophages,endothelial clls,and B cells,which were separately divided into new cell clusters by glycogen metabolism gene annotation.Pseudo temporal trajectory analysis demonstrated the temporal differentiation trajectory of different glycogen subtype cell dusters.Cellular communication analysis revealed extensive interactions between endothelial cells with glycogen metabolizing TME cell.related subtypes and diferent glycogen subtype cell clusters.SCENIC analysis of transcription factors upstream of TME cell clusters with different glycogen metabolism.In addition,TME cell dusters of glycogen metabolism were found to be enriched in expression in CAF subtypes,CD8 depleted,M1,and M2 types.Bulk seq analysis showed the prognostic signifcance of glycogen metabolism.mediated TME cell dusters in HCC,while a significant immune response was found in the immunotherapy cohort in patients treated with immune checkpoint blockade(ICB),especially for CAFs,T cells,and macrophages In summary,our study reveals for the first time that glycogen metabolism mediates intercellular communication in the hepatocellular carcinoma microenvironment while elucidating the anti-tumor mechanisms and immune prognostic responses of different subtypes of cell dusters.

GRIK1 promotes glioblastoma malignancy and is a novel prognostic factor of poor prognosis

Primary tumors of the central nervous system(CNS)are classified into over 100 different histological types.The most common type of glioma is derived from astrocytes,and the most invasive glioblastoma(WHO IV)accounts for over 57%of these tumors.Glioblastoma(GBM)is the most common and fatal tumor of the CNS,with strong growth and invasion capabilities,which makes complete surgical resection almost impossible.Despite various treatment methods such as surgery,radiotherapy,and chemotherapy,glioma is still an incurable disease,and the median survival time of patients with GBM is shorter than 15 months.Thus,molecular mechanisms of GBM characteristic invasive growth need to be clarified to improve the poor prognosis.Glutamate ionotropic receptor kainate type subunit 1(GRIK1)is essential for brain function and is involved in many mental and neurological diseases.However,GRIK1’s pathogenic roles and mechanisms in GBM are still unknown.Single-nuclear RNA sequencing of primary and recurrent GBM samples revealed that GRIK1 expression was noticeably higher in the recurrent samples.Moreover,immunohistochemical staining of an array of GBM samples showed that high levels of GRIK1 correlated with poor prognosis of GBM,consistent with The Cancer Genome Atlas database.Knockdown of GRIK1 retarded GBM cells growth,migration,and invasion.Taken together,these findings show that GRIK1 is a unique and important component in the development of GBM and may be considered as a biomarker for the diagnosis and therapy in individuals with GBM.

A prognosis model for predicting immunotherapy response of esophageal cancer based on oxidative stress-related signatures

Oxidative stress(OS)is intimately associated with tumorigenesis and has been considered a potential therapeutic strategy.However,the OS-associated therapeutic target for esophageal squamous cell carcinoma(ESCC)remains unconfirmed.In our study,gene expression data of ESCC and clinical information from public databases were downloaded.Through LASSO-Cox regression analysis,a risk score(RS)signature map of prognosis was constructed and performed external verification with the GSE53625 cohort.The ESTIMATE,xCell,CIBERSORT,TIMER,and ImmuCellAI algorithms were employed to analyze infiltrating immune cells and generate an immune microenvironment(IM).Afterward,functional enrichment analysis clarified the underlying mechanism of the model.Nomogram was utilized for forecasting the survival rate of individual ESCC cases.As a result,we successfully constructed an OS-related genes(OSRGs)model and found that the survival rate of high-risk groups was lower than that of low-risk groups.The AUC of the ROC verified the strong prediction performance of the signal in these two cohorts further.According to independent prognostic analysis,the RS was identified as an independent risk factor for ESCC.The nomogram and follow-up data revealed that the RS possesses favorable predictive value for the prognosis of ESCC patients.qRT-PCR detection demonstrated increased expression of MPC1,COX6C,CYB5R3,CASP7,and CYCS in esophageal cancer patients.In conclusion,we have constructed an OSRGs model for ESCC to predict patients’prognosis,offering a novel insight into the potential application of the OSRGs model in ESCC.